What is synthetic research?

Synthetic research uses AI-powered personas that simulate how real buyers, customers, or market segments would respond to your research questions. It produces directional signal — insights to sharpen your hypotheses — before you invest in real primary fieldwork. Gather Synthetic runs AI-moderated interviews across any audience archetype in minutes, not weeks.

How is synthetic research different from real research?

Synthetic research generates directional signal using AI personas, while real primary research collects data from actual people. Synthetic pre-research is faster (minutes vs. weeks), cheaper, and ideal for hypothesis generation and stakeholder alignment. It is not statistically valid and should be used to focus and prioritize real fieldwork, not replace it. Gather offers both synthetic pre-research and real AI-moderated interviews with actual respondents.

What types of research can Gather Synthetic run?

Gather Synthetic supports 14 study types: Brand Perception, Product Feedback, Concept Testing, Competitive Intelligence, CX/NPS Deep Dive, Messaging & Claims Testing, Win/Loss Analysis, Market Segmentation, Pricing Research, Ad & Creative Testing, Customer Journey Mapping, Feature Prioritization, Churn & Retention Analysis, and Audience Discovery.

How much does synthetic research cost?

The first 5 synthetic interviews are free. After that, B2C audience interviews cost $0.50 each and B2B audience interviews cost $5.00 each. There is no subscription required.

How accurate is synthetic research?

Synthetic research is directional, not statistically accurate. Confidence scores reflect internal AI response consistency, not statistical significance. Quantitative projections carry a ±15–20% margin of error. Treat findings as educated hypotheses to validate with real primary research, not as definitive measurements.

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Enterprise search & knowledge discovery · PUBLIC RESEARCH BRIEF

Dropbox DashWhich enterprise-search answer is trustworthy enough to act on?

Dropbox Dash says it can search shared team knowledge across connected apps, use universal search for files and media, generate sourced answers from content, and organize context for sharing through Stacks. This brief studies how employees judge freshness, authority and permissions before using a cross-app answer; it does not assume retrieval creates correct knowledge.

Sources checked 2026-09-24 · Simulation results not yet generated

Test a question in Gather ↗Explore fictional demo →

CHANGE ONE THING. LEARN WHAT MATTERS.

Three questions for the GTM team.

For a cross-app question in Dropbox Dash, would an answer with inline source snippets or a result list grouped by authoritative system help an employee reach the more accurate conclusion? Include conflicting and stale documents and score whether participants detect them.

Set up this study →

When Dropbox Dash finds multiple versions of a file, would ranking by recency or by designated owner and approval state better prevent work from starting from the wrong artifact? Use authorized test content with an independently defined current version.

Set up this study →

For a Dropbox Dash Stack shared with a project team, would a curated context summary or a minimal set of linked source artifacts create better onboarding without exposing irrelevant material? Verify inherited permissions and allow participants to request rather than receive restricted context.

Set up this study →

PROPOSED AUDIENCE

Who should weigh in?

North American marketing, creative, operations and professional-services teams evaluating or using Dropbox Dash across multiple content systems. Include frequent searchers, knowledge owners, administrators and new employees who lack organizational context. Recruit authorized adult employees with different permission scopes. Proposed audience; no search-time or adoption result is implied.

TWO TIME HORIZONS

Trial today. A habit tomorrow?

Near term · 0–90 days

Over 0–90 days, run controlled search, version-choice and sharing tasks across approved synthetic or sanitized repositories. Measure answer accuracy, source inspection, stale-document detection, permission-safe retrieval, time to a justified conclusion and inappropriate sharing attempts. Do not index private content outside the approved study scope.

Longer term · 3–12 months

Over 3–12 months, follow consented teams as content and access change. Examine repeated searches, source freshness, wrong-version incidents, knowledge-owner maintenance, access revocation, shadow repositories and onboarding quality. Search speed or adoption alone cannot establish better decisions or information governance.

What would make the result actionable?

Use current connected-app inventory, documented permissions, authorized content snapshots, version and owner ground truth and independent review of answers. Exclude secrets and unnecessary personal data, test sharing in a safe workspace and verify revocation. Any productivity or risk claim needs observed decisions and incidents, not simulated confidence.

A Gather simulation returns hypothetical customer reactions. Quantifying revenue, traffic or retention needs actual business inputs and validation against observed behavior.

Public sources

Dropbox Dash universal search, answers and Stacks overview ↗Current product page; checked 2026-09-24